The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.
It is becoming increasingly important in battlefield applications to be able to timely geolocate threat emitters existing on the battlefield. Such threat emitters often are using communication devices emitting various forms of signals, typically acoustic or electromagnetic wave signals. Intercepting these signals and forwarding them through a network into a geolocation processor requires an efficient means of exchanging the signal data being transmitted. The usual method of exchange typically involves an inefficient intermediate frequency (IF) representation of a portion of the signal received. This IF representation may even be compressed using either lossless or lossy compression algorithms. However, with lossless compression, it is difficult or impossible to achieve the desired higher compression ratios. Lossy methods compress each signal individually (without regard for all the other similar signals being transmitted) and then decompress them upon reception before correlation. So again, with lossy methods, it is also difficult or impossible to achieve higher compression ratios.
With the widespread, continuing use of relatively low bandwidth networks in battlefield applications, the network itself is increasingly becoming a “choke point” that prevents the wider use of cooperative geolocation techniques. In a practical sense, this may prevent many of the commanders within the battlefield space from using the network to acquire information from a wide variety of ground, air and national assets for use in decision making processes.
Precision cooperative geolocation using time difference of arrival (TDOA) and frequency difference of arrival (FDOA) requires coordinated processing of shared information across multiple platforms within the battlefield. Presently, this involves exchanging raw, time-tagged time/space/frequency coincident IF signal receptions in order to have a chance of seeing the same signal across multiple receiving platforms communicating on the network. The reason this data exchange is needed is that cooperatively geolocating an unknown transmitted signal requires the use of correlation techniques to compute the time and/or frequency difference of arrival of the transmitted signal to pairs of displaced receivers (i.e., receivers located at different geographic locations). This same signal arrives at slightly different times (potentially with slight frequency offsets) due to the path distance difference (and slight differences in radial velocities) between the transmitter and any given pair of receivers receiving the signal. These slight differences can be inferred by correlating the two raw receptions against each other without knowing anything about the actual transmitted signal. In order to do this, each signal received must be sent to wherever the correlations are being processed. However, exchanging this raw IF information can require a great deal of network bandwidth, especially in battlefield situations where multiple, potential target transmissions must be located and evaluated simultaneously within a short time period. In a point-to-point network, exchanging “B” bits between all “N” nodes requires BN (N−1)/2 bits to be transmitted. In a broadcast network, this still requires BN bits to be transmitted. Thus, with existing systems, a significant amount of information needs to be transmitted over the network to the processing location, and this amount of information grows significantly with the number of nodes in the network transmitting information to the processing location. Thus, it would be highly beneficial to provide a cooperative geolocation system that is able to geolocate a signal source while requiring less signal information, and with less processing power being required at the processing location.